2023

Ghoreishi, Malahat; Treves, Luke; Teplov, Roman; Pynnönen, Mikko

Circular Economy (CE) business models provide solutions for sustainable development goals by closing, slowing, intensifying, de-materializing, and narrowing resource loops.  Addressing CE requires a strategic redefinition of how companies create and capture value, which leads to design a new value creation system and innovative business models. For a full circular value creation, circular products should be designed and developed specifically for repair, refurbishing and remanufacturing purposes to close the loop. Hence, companies need to radically change their business models and the way they create value towards more innovative solutions based on CE strategies. However, implementation of circular business models in business practices has not been widely utilized and requires fundamental changes within the value chain. In a successful circular value creation, a higher degree of transparency and high-quality data for the entire value chain is required for further development of the products and processes, hence enabling design optimization and management of supply chain. Recent debates show that Artificial intelligence (AI) can be considered as an enabler of CE to help companies in innovating circular business models. Different applications of AI such as machine learning, automation and robotics, and machine visions have the capability of collecting, analysing and storing digital data. AI-enhanced products and services can tackle environmental problems through independent interactions with their surroundings and self-learning capabilities, which results in improved environmental performance characteristics.  In this chapter, we identify the role of AI in circular value creation for sustainable development goals.